Boiling Phenomenon and Bubble Formation CFD Tutorial

$300.00 Student Discount

In this project, Boiling Phenomenon to investigate three-volume fraction discretization methods has been simulated and the results of this simulation have been investigated.

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Description

Boiling Phenomenon and Bubble Formation, Ansys Fluent CFD Simulation Training

Boiling is the fast evaporation of a liquid when heated to its boiling point. The temperature at which the liquid’s vapor pressure equals the pressure exerted on the liquid by the surrounding environment. Boiling may be classified into two types: nucleate boiling, in which tiny bubbles of vapor develop at distinct places, and critical heat flux boiling, in which the boiling surface is heated above a specific critical temperature and a film of vapor forms on the surface. Transition boiling is an unstable intermediate form of boiling that has components of both forms. The boiling point of water is 100 °C or 212 °F; however, it is lower at higher altitudes due to reduced air pressure. Boiling Phenomenon and Bubble Formation CFD simulation by ANSYS Fluent is carried out in this product.

Boiling

Project Description

In this simulation, the difference between HRIC-compressive-Geo-reconstruct models and their effect on the output results were discussed by changing the volume fraction discretization. The computational domain is a 15 x 15 cm cube with a 2 x 2 cm heated surface. The change in volume fraction discretization showed no significant change in surface temperature and heat transfer coefficient. Only the Geo-Reconstruct model visually models a more realistic simulation with a higher computational cost.

Geometry & Mesh

The computational domain was designed using Design Modeler software. The computational domain includes a 15 x 15 cube with a 2 x 2 cm heating surface.

Boiling

Ansys Meshing software was used for grid generation, and the type of problem elements was structured. Also, the total number of elements was about 570000.

CFD Simulation Solver Setting

In this simulation, the following hypotheses are established:

  • A pressure solver was used.
  • The problem was solved transient
  • An explicit VOF multiphase model was activated.
  • Gravitational and capillary effects were considered.

Also, the table below shows the characteristics and values of boundary conditions, along with the models and hypotheses.

Material Properties
Water
Amount Fluid properties
998.2 Density (kg/m3)
Water vapor
Amount Fluid properties
0.5542 Density (kg/m3)
Multiphase
Homogeneous model VOF (volume of fluid)
Number of Eulerian phases 2 (water-water vapor)
Interface modeling sharp
Formulation Explicit
Phase interaction
Evaporation & Condensation Lee model
From phase Frequency (1/s) 10
Fluid type Surface tension coefficient (N/m)
Water-vapor 0.06
Boundary Condition
Type Heat flux (W/m^2)
Hot wall 10000
Cell zone condition
Fluid mixture
Turbulence models
K-  viscous model
Realizable K- model
Standard wall function Wall function
Solution methods
Coupled pressure velocity coupling
Modified body force weighted pressure spatial discretization
First-order upwind momentum
First-order upwind turbulent kinetic energy
First-order upwind      turbulent dissipation rate
Volume fraction     Geo-reconstruct

Compressive

Modified HRIC

Initialization (Standard)
0 (Pa)

 

 gauge pressure
373.15 K Temperature
1 Water volume fraction

Boiling Phenomenon and Bubble Formation Results

The table below clarifies that the average surface temperature at the input of the problem and the heat transfer coefficient in these three discretization models do not change much. In the simulation with high computational cost, it is suggested that the discretization methods of compressive and modified HRIC Be have a lower computational cost. But for near-reality simulation, it is better to use the Geo-reconstruct model, which has a higher computational cost.

Discretization method Surface temperature (K) Heat transfer coefficient (W/m^2.K)
compressive   385.835   102.398
Modified HRIC   385.688   102.547
Geo-reconstruct 387.96463 101.76327

The grid elements need to be finer near the hot surface to increase the simulation accuracy. The distance of the first cell is essential in boiling studies, but this is very effective in increasing the computational costs in 3D simulations.

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